CS7DS1 – Data Analytics
(Semester 1 & 2, 10 ECTS) To understand the theory and be able to apply the following techniques
to a set of data.
School of Computer Science and Statistics
(Semester 1 & 2, 10 ECTS) To understand the theory and be able to apply the following techniques
to a set of data.
(Semester 2, 5 ECTS)
This course covers fundamentals and state-of-the-art in augmented reality, as well
as related areas of 3D computer vision and graphics.
(Semester 1, ECTS 5) This module aims to equip the student with the knowledge and tools to visualise data in ways that give insight and understanding.
(Semester 1, 5 ECTS) This module aims to provide both a theoretical and practical understanding of urban
computing and associated cyber-physical concepts, principles, challenges and
solutions.
(Semester 1, 5 ECTS) Wave equation and its solution; Maxwell´s equations; Fourier transform and analysis; vibration; mass-spring-damper systems; numerical methods; simulation software.
(Semester 2, 5 ECTS) The objectives of this module are: to develop an in-depth understanding of risk, data
privacy, threats and risks of security breaches, an awareness of computer security
(cryptographic) and protocol techniques, and an ability to make appropriate
decisions about securing data.
(Semester 1, 5 ECTS) This module aims to provide both a theoretical and practical understanding of
modern and next generation networking and systems concepts, principles, practices
and technologies. Contemporary and emerging wired and wireless network systems
are targeted.
(Semester 2, 5 ECTS) In this module, students will explore the prevailing vision for an Internet of Things in
a practical, pragmatic manner.
(Semester 1, 5 ECTS) Explain the process of content indexing in information retrieval including stop word removal, conflation (stemming, string-comparison), and the language dependency of these methods.
(Semester 2, 5 ECTS) Appreciate the scope, applications and limitations of artificial intelligence;